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Wisdom of the Crowd

Pooling data from 30 resources enables large-scale research on how genes are regulated.

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Since its release in 2011, Dr. Jurisica’s mirDIP tool has been accessed by more than 13,500 unique users from 86 countries.

Announced on Jan 22, 2018

Crowdsourcing is a concept in which large groups of people work together to fulfill a common goal. The idea is that there is strength in numbers: as more people make individual contributions, the work that needs to be done is finished quicker.

In his own way, Krembil Senior Scientist Dr. Igor Jurisica has been applying a similar concept—called integrative computational biology—throughout his career. He is a pioneer in using this technique to create large-scale tools for the research community that integrate data from his own research and those of his peers. These tools offer pooled data to an unprecedented breadth and diversity that could not be created by one team alone.

Dr. Jurisica’s latest release is an updated version of mirDIP, the microRNA Data Integration Portal that his group introduced in 2011. It uses sophisticated computational approaches to predict which genes are controlled by microRNAs, short RNA molecules that regulate the activity of specific target genes. Given this important function, the role of microRNAs in gene-related diseases such as cancer and arthritis are of great interest to the research community. Identifying which microRNAs modify which target genes would inform the development of new therapies to enhance—or block—these interactions.

To develop the mirDIP update, Dr. Jurisica and his research team summarized the data from 30 different microRNA prediction algorithms and databases. After applying complex mathematical approaches to account for the different methodologies used by each of the databases, the team finalized a set of more than 151 million predictions—approximately 75% more predictions than the next largest microRNA prediction database—in this release focusing on human systems.

The team also developed an algorithm that assigns a score to each prediction. “This score provides users with a measure of the confidence of each prediction,” explains Dr. Jurisica. “Researchers can now access these predictions in one place—accelerating the research pipeline towards creating new therapies for diseases.”

This work was supported by the Krembil Foundation; the Ministry of Research, Innovation and Science; the Canadian Cancer Society Research Institute; the Natural Sciences and Engineering Research Council of Canada; the Canada Foundation for Innovation; the Canada Research Chairs Program; and IBM.